Artificial intelligence is very prevalent in movies and science fiction, from sentient beings that are able to walk, and talk, and live with humans like the characters from Westworld, Star Wars, or Star Trek. In reality, however, we are a far way away from the dream of sentient machines that we see and read about in science fiction. So much of today’s AI systems are doing much more mundane things that aren’t getting the attention or interest of the press and media.
However, interest and investment in AI remains strong, and even if AI is unable to live up to the fantasies of science fiction, vendors are riding the hype wave of AI and promising capabilities that AI systems might not be able to deliver. While vendors are doing their best to deliver these capabilities, the challenge is that adopters and end users sometimes themselves get caught up in the hype as well. This mismatch between what is being promised by the technology vendors and what is actually possible is a common reason why AI projects fail.
The reasons for these failures could be due to a product mismatch, overhyping or overselling on AI capabilities, or selling solutions a customer doesn’t actually need. And, it’s not only inexperienced people making mistakes and falling for this. Even experienced teams suffer AI project failures. If you blindly trust the vendors you may end up with a product that doesn’t actually fit your needs and become an AI failure statistic yourself. Despite all these challenges, organizations are still seeing success with AI systems, but not necessarily from the technology companies that you might be hearing about in the news.